High-altitude cold-desert ecosystems in the western Himalayas are increasingly exposed to atmospherically transported heavy metals, yet the bioaerosol-mediated deposition pathway and its coupling with biospheric response remain poorly quantified. This study presents a multi-scale framework linking satellite-derived Aerosol Optical Depth (AOD) to field-measured sediment metal concentrations (Cr, Ni, As, Cd, Pb) and vegetation stress indices across Pin Valley National Park (PV-NP), Himachal Pradesh, India. We integrate two field campaigns (2022, 2023) comprising ICP-MS analysis of water, sediment, and bioaerosol samples with a 25-year Google Earth Engine time-series archive (2000–2024) of MODIS and Sentinel-2/Landsat-derived spectral indices. Empirical Mode Decomposition followed by PCA—adapted from Antarctic ice-sheet studies—extracts inter-annual variability revealing dominant 4–8 year periodicities broadly consistent with ENSO teleconnections. Leave-one-out cross-validated (LOOCV) machine-learning models, benchmarked with 1000-replicate bootstrap confidence intervals on <em>R<sup>2</sup><sub>LOO</sub></em> and Monte Carlo error propagation, evaluate the predictive capacity of remote-sensing features for sediment metal concentrations. Results indicate that AOD and its 30-day lag carry contamination-relevant signal (Cr–Ni dominant) but predictive skill at <em>n</em> = 11–14 is bounded by sample size: bootstrap 95% CIs cross zero for all ten metal–year targets and the strongest target (Ni-2022) yields permutation <em>p</em> = 0.061. At the site scale, hotspot clusters (PLI ≥ <em>Q<sub>75</sub></em>) show directional shifts across six vegetation indices consistent with metal-induced stress (ΔNDVI = −0.004, ΔNDRE = −0.017, ΔPSRI = +0.049, ΔLST = +1.64<sup>◦</sup>C, pooled 2022–2023), but at <em>n<sub>h</sub></em> = 7 vs. <em>n<sub>nh</sub></em> = 18 individual contrasts do not reach <em>p</em> < 0.05 (joint sign-test <em>p</em> = 0.031). Site-level LST–NDVI Pearson correlation is positive (<em>r</em> = +0.46, <em>p</em> = 0.020, pooled), reflecting elevation co-control in this energy-limited cold desert— an inversion of the canonical water-limited LST–NDVI coupling. This integrated atmosphere–lithosphere–biosphere approach advances remote-sensing methodologies for environmental management in fragile Himalayan ecosystems while honestly delimiting the small-sample regime.